Outbreaks of arthropod-borne viruses, such as dengue (DENV) and chikungunya (CHIKV), demonstrate the substantial cost and health burden of these emerging/re-emerging health threats to the developing and developed world. Africa's population growth, unplanned urbanization, habitat destruction, and trans-border travel are likely contributing to a rise in arboviral outbreaks. In sub-Saharan Africa, routine passive surveillance for these diseases detects only a fraction of their impact, given the high probability of misdiagnosis and unknown levels of transmission across different landscapes and within different susceptible populations. Preliminary data demonstrate that Kenyan children and adults are frequently exposed to DENV and CHIKV, both between and during known outbreaks. We hypothesize that sporadic transmission, mild forms of disease, and/or misdiagnosis likely contribute to under-recognition of circulation in less-developed settings, while still leaving potential for large epidemics of major economic importance. We propose to obtain estimates of transmission and infection for DENV strains 1 through 4 (DENVI-4) and CHIKV across Kenya. Our objectives are to assess the true burden of CHIKV- and DENV-related human exposure in two regions of Kenya that represent varied landscape, climate, and populations and then to determine the spatial and temporal patterns of transmission. Using several novel approaches, we will address the following aims: 1) Quantify the prevalence of human exposure to CHIKV and DENV1-4 in two regions of Kenya. 2) Detect and predict spatial and temporal patterns of CHIKV and DENV transmission in rural settings by integrating data on circulation in humans (Aim 1) with environmental and weather/climate data collected both in situ and using satellite imagery. The research involves cohorts in and near Msambweni (coastal) and Masalani (northeastern), Kenya, where there is year-round transmission of arboviruses, and is based on 10 years of collaborative longitudinal studies. Methodologies include analyses of the relationship between well-defined clinical and epidemiologic findings with immune biomarkers of virus exposure. In this project we will couple data from previous long-term studies on the Kenyan coast and in Northeastern Kenya to fill fundamental knowledge gaps about the persistence of CHIKV and DENV in nature, including the ecologic factors that drive persistence during interepidemic cycles. We will then integrate community-level human prevalence data with environmental data to determine the likely drivers of local human transmission. Our planned modeling synthesis of climate data with human data is expected to contribute to improved understanding of CHIKV and DENV burden and outbreaks in the East African landscape. This knowledge is essential for a full understanding of transmission and to optimize prevention and control programs.